| Popis: |
In this paper, we propose an algorithm estimating the vanishing point (VP) of a sidewalk in a man-made environment from a single image. For finding the VP, the lines in an image are efficiently exploited as a clue because the projections of parallel lines in an image intersect at a VP. However, there are too many noises disturbing line detection in natural scene images, for example trees, pedestrian and shadows. Thus, we suggest a noise reduction technique called orientation consistency pass filtering (OCPF) for improving line detection performance. An edge orientation at the window center of OCPF is compared to its neighbor edge orientations for calculating orientation difference. The center pixel is removed if the difference of edge orientations greater than a threshold, and preserved otherwise. In addition, we suggest a novel vanishing point detection method using edge orientation voting (EOV), which predict VP position accurately. The lines filtered by OCPF can generate the VP candidates using bottom-up extended lines. The VP candidates receive supports from all edges below the currently inspected VP candidate. The most supported VP candidate is selected as dominant VP. This proposed method was implemented and tested on 600 sidewalk image database that has 640x320 resolutions. 74.3 % of the test sidewalk images are in range from 0 pixels to 20 pixels from manually marked VP. |
